Boost Outbound with AI: Define ICP, Prioritize Accounts, and Research

Apollo.io just acquired Pocus! Feels like an inflection point for how GTM actually works. Pocus has been building around a simple idea: product usage should drive revenue decisions. Not dashboards. Not gut feel. Actual behavior. For a long time, GTM has been split: - Sales works out of CRM + outreach tools - Product data lives somewhere else entirely The companies that win are the ones that connect those two. Most teams don’t, not because they don’t want to, but because it’s hard. This starts to close that gap. Apollo already has: - Data (who to target) - Engagement (how to reach them) - Execution (how deals move forward) Pocus adds the missing piece: - Product signals (when something actually matters) That changes the motion. Instead of guessing who might be ready: - You see who is already showing intent - You understand what they’re doing in the product - You act with context, not just a list It’s a shift from lead-based GTM to behavior-based GTM. Curious to see how this plays out over the next year.

New year. New planning cycles. Same AI mistake. Too many teams still treat AI like software you INSTALL. Not something you OPERATE. In this clip from Season 4 of the 10x GTM podcast Mollie B. said something that’s a helpful reminder to anyone implementing AI in 2026: “AI is not a set-it-and-forget-it thing. You have to think about it like a baby. You’re growing and nurturing it.” Because the real unlock with AI isn’t: ➡️turning it on ➡️adding another model ➡️ shipping a flashy feature It’s building the operational muscle around it. Ask yourself these questions to understand if you’re prepared 1. How are you feeding it new information as your product evolves? 2. What QA exists to catch hallucinations or inconsistencies? 3. What’s your risk tolerance for being wrong especially in any customer-facing workflows? AI learns. It drifts. It reflects the systems (and discipline) around it. If you’re doing annual planning right now, the question isn’t “What new AI tools should we launch?” It’s “What practices do we need to support AI over time?” Catch up on all of season 4 everywhere you listen (or watch) podcasts Youtube: https://lnkd.in/edaj9Tav Spotify: https://lnkd.in/eUizEAei

For years, the GTM tool debate was about which platform reps should live in. CRM vs. SEP. Native vs. best-of-breed. Everyone’s fighting to be the destination. In an AI-native world, that's the wrong fight. What actually moves the needle isn't where a rep works. It's whether they have the right data, the right context, and intelligence that tells them exactly what to do next…wherever they happen to be. If a rep wants to live in Apollo, great. If they want to work out of Claude, ChatGPT, or their browser, also great. The system should flex to them, not the other way around. The numbers are telling us the field already knows this: - 11,000 teams using Apollo inside Claude, ChatGPT, and Perplexity - 6M+ calls to our data through AI tools - 1M+ people using Apollo in their browser None of that happened inside our UI. The teams winning right now aren't the ones with the prettiest platform. They're the ones with data and intelligence that travels – that shows up wherever a rep is already working and tells them what to do. The interface is flexible but the foundation isn't. #ApolloAnywhere

I was wrong. When I said signals were commoditized, maybe that was a bit premature. Here’s what i’m seeing articulated more clearly What's actually commoditized is ACCESS to the signal. Job changes, promotions, content engagement. You can buy that from 10+ vendors today. Same data. What's NOT commoditized is what happens next. How do you actually ACTIVATE that signal and orchestrate it within your workflows. This isn’t commoditized, teams are still missing out on signal gold because it’s buried in siloed tools. I'm in this space every day at Pocus, and the gap I see isn't between who has the signal and who doesn't. It's between who can actually activate that signal in a rep's workflow at the right moment, with all the additional context a rep needs (contacts, research, and messaging). And most teams are failing at that part. The proof is everywhere. Someone changes jobs at a target account and either: 1/Nothing happens (the signal dies in a dashboard nobody checks) 2/ A generic "congrats on the new role!" lands 2 months late 3/ A "personalized" sequence fires that's clearly a template with [FIRST_NAME] swapped in I leave signal breadcrumbs everywhere. LinkedIn posts, podcast episodes, a very public job history. I can count on 1 hand the number or reps who actually use it to send me something timely and relevant. The "signals are commoditized" narrative conflates data availability with execution quality. Most signals are table stakes. The way they get actioned (workflow, the copy, the timing), that's where the game is still wide open.

We had 33 different signals firing for our SDRs. Funding rounds. Hiring alerts. Website visits. G2 intent. LinkedIn engagement. Product usage. Job changes. Content downloads. Our reps were drowning. They'd log into their dashboard, see 100+ accounts lighting up, and freeze. Decision paralysis. Pipeline attainment: 33%. So we did something counterintuitive: We cut 85% of our signals. Here's what we learned: Not all signals are created equal. Some signals are alarm bells 🚨They need immediate response within 2-4 hours ☑️G2 intent ☑️Demo page visits ☑️Pricing page views These mean someone is actively shopping RIGHT NOW. Other signals are just nudges 👉They're informative but not urgent ☑️LinkedIn engagement ☑️Blog reads ☑️Hiring signals We kept 3-5 high-SLA signals and built prescriptive plays around them.  ____ RESULTS  → $4.8M in pipeline generated from just those 3-5 core signals in 90 days. → 471% pipeline increase in 2025 → 70% S0 → S2 conversion (up from 25%) → Reps hitting 100%+ quota for 2 quarters straight ____ Today we are releasing our Account-Based Prospecting Playbook with the exact signal framework we use at Pocus. You'll see which signals actually drive meetings, how to build SLAs around them, and how to stop overwhelming your reps with noise. Link in comments 👇

🚀 Big news: Apollo is acquiring Pocus! 🤩 Imagine a world 🌎 where your go-to-market team doesn't just see signals—they instantly know exactly what to do next. Where AI doesn't just suggest, but orchestrates. 🎺 Where your sales reps spend zero time wondering "who should I call today?" and 100% of their time on the deals that actually matter. That's the world we're building. 🏗️ Today marks a massive step forward in Apollo's mission to create the AI-native operating system for GTM teams—from scrappy startups to Fortune 500s. 🚀 By bringing Pocus (the revenue intelligence platform trusted by Canva, Asana, and monday.com) into the Apollo family, we're combining: 🔮 230M+ contacts in Apollo's living data network ⚡ Pocus' enterprise-grade signal intelligence 🤖 AI-powered orchestration that turns raw data into intelligent action What this means for you: 🤷♂️ ✅ For our 600K+ customers and millions of users globally—everything you love about Apollo stays exactly the same. Now, what's under the hood you ask.....? Ferrari like engine that is ready to hit the tracks in the near future. 🏎️ 💨 We're building something that's never existed before: a unified AI powerhouse that detects: 💰 Buying signals 💰 Prioritizes your highest-value accounts 💰 Guiding execution—all in one seamless platform The traditional GTM tech stack? Consider it officially obsolete. 🏚️→🚀 -------- As our CEO Matt Curl put it: 💬 "This accelerates our vision to empower teams to execute with precision and speed at a level that's never been possible before." -------- The future of go-to-market isn't a collection of point solutions duct-taped together. It's one intelligent system. And that future just got a lot closer. Here's to the next chapter! 🥂 #sales #marketing #operations #ai #gtm

I'll admit it: before the acquisition, I wasn't sure Apollo.io actually got prospecting. Because at Pocus relevance selling was the whole religion. Not "more volume” or "more sequences” but knowing exactly why THIS account, right now and saying something that actually lands because of it. We built an entire company on the belief that reps drowning in generic outreach was a solvable problem, not just the cost of doing sales. So when the acquisition happened, one of the first things I was thinking about was… does this company actually understand that prospecting isn't a volume problem, it's a relevance problem? Or is it just a big database people rent contacts from and hope for the best? Then I got inside it, and yeah. They got it. Which is why I said yes. Our new AI GTM Survey backs up what I already believed walking in: 84% of GTM teams are now using AI for prospecting and research, miles ahead of personalization or enrichment. Everyone's finally catching up to something obvious. Reps don't need more names… they need to know which names actually matter and why. What's crazy is that only 17% say their AI prospecting is actually fully operational and measured. Most teams slapped AI onto the same old spray-and-pray motion and called it innovation. Closing that gap, turning "more AI" into "smarter targeting," is exactly the work I came to Apollo to do. And it’s been more fun than I expected as we build out this AI GTM system. Full survey's live if you want the rest of the stats. Link in comments.

Apollo 🤝 Pocus🔮 Big news - Apollo just acquired Pocus — and it’s a strong signal of where we’re going! This isn’t about incremental change. It’s a clear investment in what the next generation of GTM looks like: more signal-driven, more intelligent, and more aligned to how modern teams actually operate. Pocus has been building some of the most compelling product-led and data-driven workflows in the space. Bringing that into Apollo accelerates our ability to help customers move from static outreach to truly dynamic GTM execution. Two teams, one direction: redefining how companies find, prioritize, and convert the right opportunities. So proud to be a part of this momentum! This story is worth a look → https://bit.ly/4bFcbfH

Alexa Grabell, CEO of Pocus, and Matt Curl, 𝐂𝐄𝐎 of 𝗔𝗽𝗼𝗹𝗹𝗼.𝗶𝗼, Lead the Next Phase of AI-Native GTM Innovation   Alexa Grabell, CEO of Pocus, joins forces with Matt Curl, 𝐂𝐄𝐎 of Apollo.io, as Apollo acquires Pocus to enhance its AI-driven revenue intelligence capabilities. The integration enables GTM teams to detect buying signals, prioritize accounts, and execute with precision all within a single, unified platform. With 400%+ enterprise account growth over the past year, including clients such as Anthropic and Glean, this acquisition accelerates Apollo’s vision for an AI-powered GTM operating system.   How will the combination of Apollo’s scale and Pocus’ AI-native signal intelligence transform revenue operations and go-to-market effectiveness?   Read the full story on Rev Tech News: https://lnkd.in/dFeUCs4E   #ApolloIO #Pocus #AlexaGrabell #MattCurl #AINativeGTM #RevenueIntelligence #SalesTech #MarTech #GTMStrategy #EnterpriseGrowth #AIinSales #RevOps #RevTechNews

Most GTM inefficiency doesn’t come from bad reps or bad strategy. It comes from stack sprawl: ❌Two intent tools answering the same question ❌Three data sources feeding slightly different fields ❌No one confident which signal should actually drive action We built a free GTM Tech Stack Analyzer to help teams get a fast, honest snapshot of where their stack falls short today. We’ve already had HUNDREDS of you try the tool and here’s what we’ve learned so far: 1/ Where tools overlap - So far the biggest areas of overlap have been intent + data providers. Aggregating signals in one tool could save you $$$. 2/ Identify gaps - smaller teams are missing revenue forecasting (i.e. Gong, Clari). Most are missing a signal aggregation and orchestration tool (i.e. Pocus). 3/ Biggest savings - Reducing the number of data and intent tools If you’re responsible for keeping the stack sane, try our tool to see your grade 👉 https://lnkd.in/eXXK8-Fp Note: GTM Tech Stack Analyzer is built with the help of our pals at Lovable and is best used as a starting point for analysis. We’re constantly iterating, so if you have feedback, send us your thoughts!